


'''simple docstring'''


import os
import textwrap

import pyarrow as pa
import pytest

from datasets import ClassLabel, Features, Image
from datasets.packaged_modules.csv.csv import Csv

from ..utils import require_pil







@pytest.fixture
def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= tmp_path / """file.csv"""
				_SCREAMING_SNAKE_CASE					:			List[Any]							= textwrap.dedent(
				    """\
        header1,header2
        1,2
        10,20
        """	)
				with open(SCREAMING_SNAKE_CASE__				, """w"""	) as f:
								f.write(SCREAMING_SNAKE_CASE__	)
				return str(SCREAMING_SNAKE_CASE__	)







@pytest.fixture
def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			str							= tmp_path / """malformed_file.csv"""
				_SCREAMING_SNAKE_CASE					:			List[str]							= textwrap.dedent(
				    """\
        header1,header2
        1,2
        10,20,
        """	)
				with open(SCREAMING_SNAKE_CASE__				, """w"""	) as f:
								f.write(SCREAMING_SNAKE_CASE__	)
				return str(SCREAMING_SNAKE_CASE__	)







@pytest.fixture
def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Tuple							= tmp_path / """csv_with_image.csv"""
				_SCREAMING_SNAKE_CASE					:			Dict							= textwrap.dedent(
				    f"""\
        image
        {image_file}
        """	)
				with open(SCREAMING_SNAKE_CASE__				, """w"""	) as f:
								f.write(SCREAMING_SNAKE_CASE__	)
				return str(SCREAMING_SNAKE_CASE__	)







@pytest.fixture
def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= tmp_path / """csv_with_label.csv"""
				_SCREAMING_SNAKE_CASE					:			Optional[int]							= textwrap.dedent(
				    """\
        label
        good
        bad
        good
        """	)
				with open(SCREAMING_SNAKE_CASE__				, """w"""	) as f:
								f.write(SCREAMING_SNAKE_CASE__	)
				return str(SCREAMING_SNAKE_CASE__	)







@pytest.fixture
def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Any							= tmp_path / """csv_with_int_list.csv"""
				_SCREAMING_SNAKE_CASE					:			Optional[Any]							= textwrap.dedent(
				    """\
        int_list
        1 2 3
        4 5 6
        7 8 9
        """	)
				with open(SCREAMING_SNAKE_CASE__				, """w"""	) as f:
								f.write(SCREAMING_SNAKE_CASE__	)
				return str(SCREAMING_SNAKE_CASE__	)







def      snake_case_  (    SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__				, SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Optional[int]							= Csv()
				_SCREAMING_SNAKE_CASE					:			List[Any]							= csv._generate_tables([[csv_file, malformed_csv_file]]	)
				with pytest.raises(SCREAMING_SNAKE_CASE__				, match="""Error tokenizing data"""	):
								for _ in generator:
												pass
				assert any(
				    record.levelname == """ERROR"""
				    and """Failed to read file""" in record.message
				    and os.path.basename(SCREAMING_SNAKE_CASE__	) in record.message
				    for record in caplog.records	)







@require_pil
def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				with open(SCREAMING_SNAKE_CASE__				, encoding="""utf-8"""	) as f:
								_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= f.read().splitlines()[1]
				_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= Csv(encoding="""utf-8"""				, features=Features({"""image""": Image()}	)	)
				_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= csv._generate_tables([[csv_file_with_image]]	)
				_SCREAMING_SNAKE_CASE					:			int							= pa.concat_tables([table for _, table in generator]	)
				assert pa_table.schema.field("""image"""	).type == Image()()
				_SCREAMING_SNAKE_CASE					:			List[Any]							= pa_table.to_pydict()["""image"""]
				assert generated_content == [{"path": image_file, "bytes": None}]







def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				with open(SCREAMING_SNAKE_CASE__				, encoding="""utf-8"""	) as f:
								_SCREAMING_SNAKE_CASE					:			List[str]							= f.read().splitlines()[1:]
				_SCREAMING_SNAKE_CASE					:			str							= Csv(encoding="""utf-8"""				, features=Features({"""label""": ClassLabel(names=["""good""", """bad"""]	)}	)	)
				_SCREAMING_SNAKE_CASE					:			List[str]							= csv._generate_tables([[csv_file_with_label]]	)
				_SCREAMING_SNAKE_CASE					:			int							= pa.concat_tables([table for _, table in generator]	)
				assert pa_table.schema.field("""label"""	).type == ClassLabel(names=["""good""", """bad"""]	)()
				_SCREAMING_SNAKE_CASE					:			List[Any]							= pa_table.to_pydict()["""label"""]
				assert generated_content == [ClassLabel(names=["""good""", """bad"""]	).straint(SCREAMING_SNAKE_CASE__	) for label in labels]







def      snake_case_  (    SCREAMING_SNAKE_CASE__	):







				"""simple docstring"""





				_SCREAMING_SNAKE_CASE					:			Dict							= Csv(encoding="""utf-8"""				, sep=""","""				, converters={"""int_list""": lambda SCREAMING_SNAKE_CASE__	: [int(SCREAMING_SNAKE_CASE__	) for i in x.split()]}	)
				_SCREAMING_SNAKE_CASE					:			List[Any]							= csv._generate_tables([[csv_file_with_int_list]]	)
				_SCREAMING_SNAKE_CASE					:			List[str]							= pa.concat_tables([table for _, table in generator]	)
				assert pa.types.is_list(pa_table.schema.field("""int_list"""	).type	)
				_SCREAMING_SNAKE_CASE					:			Any							= pa_table.to_pydict()["""int_list"""]
				assert generated_content == [[1, 2, 3], [4, 5, 6], [7, 8, 9]]








'''simple docstring'''


import tempfile
import unittest

from make_student import create_student_by_copying_alternating_layers

from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch


UpperCAmelCase_						:  List[Any]				  =						'sshleifer/bart-tiny-random'
UpperCAmelCase_						:  Tuple				  =						'patrickvonplaten/t5-tiny-random'





@require_torch
class        lowercase__    (		unittest.TestCase   ):





							'''simple docstring'''


							@cached_property
							def UpperCAmelCase_      (       self    ):
											return AutoConfig.from_pretrained(__snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			int							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=1    )
											self.assertEqual(student.config.num_hidden_layers       ,   1    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			int							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=__snake_case    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			str							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=__snake_case    )
											self.assertEqual(student.config.encoder_layers       ,   1    )
											self.assertEqual(student.config.decoder_layers       ,   self.teacher_config.encoder_layers    )






							def UpperCAmelCase_      (       self    ):
											_SCREAMING_SNAKE_CASE						,			*_SCREAMING_SNAKE_CASE					:			Union[str, Any]							= create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=1       ,   d=1    )
											self.assertEqual(student.config.encoder_layers       ,   1    )
											self.assertEqual(student.config.decoder_layers       ,   1    )






							def UpperCAmelCase_      (       self    ):
											with self.assertRaises(__snake_case    ):
															create_student_by_copying_alternating_layers(__snake_case       ,   tempfile.mkdtemp()       ,   e=__snake_case       ,   d=__snake_case    )




